Hepatitis C virus (HCV) infection and HCV-HIV coinfections are significant causes of morbidity and mortality among people who inject drugs (PWID). HCV prevalence among PWID can exceed 90% in high burden settings, and incidence remains high in the US following the changing epidemiology of substance use disorders. Highly effective, curative treatment for HCV is available, and calls have been made for the expansion of treatment-as- prevention and harm reduction programs to eliminate HCV globally. While modeling studies have indicated moderate to high treatment coverage may achieve elimination targets among PWID by 2030, such models often do not fully account for individual heterogeneity and longitudinal patterns in HCV risk. Even low rates of HCV reinfection can lead to pathogen persistence, a phenomenon that may be particularly important when considering micro-elimination among PWID living with HIV. However, traditional methods to measure HCV risk result in substantial misclassification when long testing intervals lead to frequent unobserved HCV exposure events (e.g., clearance-reinfection events occurring between study visits classified as a single chronic infection). Here, we will leverage rich epidemiologic and molecular data from a 30-year cohort of HIV-infected and uninfected PWID in Baltimore, MD USA (the ALIVE study) to explore the feasibility of HCV elimination in a high burden setting. We will use hidden Markov models which account for unobserved exposures to estimate HCV risk across individuals' injection careers. We will use next-generation genetic sequencing data to quantify risk of reinfection and treatment failure among individuals known to have received directly acting antiviral therapy and returned with post-treatment viremia. In both aims, we will consider the role of HIV coinfection as a modifier of HCV risk. Together, these aims will allow for identification of individuals and time periods within injection careers in which expected HCV reinfection risk is high. With this improved understanding of the individual and temporal variance in HCV reinfection risk, we will generate evidence-based assessments of various policies and strategies for delivering HCV treatment and harm reduction using dynamic transmission models, including targeted strategies among HIV-infected PWID. This project will provide critical guidance for policymakers and public health officials on the design and implementation of effective HCV elimination strategies among HIV-infected and uninfected PWID.